The video tutorial explains the use of Hbase as a non-relational database on EMR, highlighting its ability to handle petabyte-scale data across Hadoop clusters. It compares Hbase with DynamoDB, noting that while both are Nosql databases, DynamoDB offers advantages like being fully managed and serverless, with better AWS integration. However, Hbase is preferable for certain use cases, such as handling sparse data and high-frequency counters. The tutorial also discusses AWS's integration of Hbase with EMR and S3, providing flexibility in data storage and backup.

What is the primary function of Hbase in a Hadoop cluster?

• To handle petabyte-scale data across clusters

• To manage relational databases

• To offer high-level data analytics

• To provide a serverless computing environment

Which of the following is a key advantage of using DynamoDB over Hbase on AWS?

• DynamoDB supports SQL queries natively

• DynamoDB is fully managed and serverless

• DynamoDB offers better integration with Hadoop

• DynamoDB is open-source

What is a significant benefit of using DynamoDB for AWS users?

• It is better for high-frequency counters

• It offers consistent reads and writes

• It is based on Google technology

• It provides extensive integration with AWS services

Why might Hbase be a better choice than DynamoDB for certain applications?

• Hbase is cheaper than DynamoDB

• Hbase is easier to set up

• Hbase offers better integration with AWS services

• Hbase handles sparse data more effectively

In what scenario is Hbase particularly advantageous over DynamoDB?

• When requiring serverless architecture

• When needing automatic scaling

• When needing high write and update throughput

• When integrating with AWS Glue